ObjectiveTo explore the target of Erzhiwan in reducing myocardial injury in ovariectomized mice through non-targeted myocardial metabolomics combined with experimental verification. MethodsOvariectomized mouse model was selected， 40 female C57BL/6 mice were randomly divided into sham operation group， model group， estrogen group（estradiol valerate， 1.3×10^-4 g·kg^-1）， Erzhiwan low and high dose groups（3.12， 9.36 g·kg^-1）， with 8 mice in each group. Each administration group was given the corresponding dose of Erzhiwan by gavage， and the sham operation group and model group were given equal volume of distilled water by gavage for 12 weeks. Echocardiography was used to detect cardiac function， hematoxylin-eosin（HE） staining was used to observe myocardial morphological changes， and enzyme-linked immunosorbent assay（ELISA） was used to detect the levels of estrogen， N-terminal pro-brain natriuretic peptide（NT-proBNP）， hypersensitive troponin T（hs-TnT）， total cholesterol（TC）， triglyceride（TG）， low density lipoprotein cholesterol（LDL-C）， high density lipoprotein cholesterol（HDL-C）， interleukin（IL）-1β， IL-18 and tumor necrosis factor-α（TNF-α）. The non-targeted metabolomics of mouse myocardium were analyzed by ultra performance liquid chromatography-quadrupole-electrostatic field orbital trap high-resolution mass spectrometry（UPLC-Q-Exactive Orbitrap MS）， and the differential metabolites and corresponding metabolic pathways were obtained. The mRNA expression levels of phosphatidylinositol 3-kinase（PI3K） and protein kinase B（Akt） in mouse myocardial tissues were detected by real-time fluorescence quantitative polymerase chain reaction（Real-time PCR）， and the protein expression levels of PI3K， Akt， phosphorylated（p）-Akt were detected by Western blot. ResultsCompared with the sham operation group， the model group showed abnormal cardiac function， increased myocardial fiber space， cardiomyocyte atrophy， sarcoplasmic aggregation， and occasional dissolution or rupture of muscle fiber， the level of estrogen in the serum was decreased， the levels of NT-proBNP， hs-TnT， IL-1β， IL-18， TNF-α， TG， TC and LDL-C were increased， and the level of HDL-C was decreased（P<0.01）. Compared with the model group， Erzhiwan could increase the level of estrogen， improve the abnormal cardiac function， reduce the pathological injury of myocardial tissue， decrease the levels of myocardial injury markers（NT-proBNP， hs-TnT） and inflammatory factors（IL-1β， IL-18， TNF-α）， decrease the levels of TG， TC， LDL-C， and increased the level of HDL-C（P<0.01）. The results of non-targeted myocardial metabolomics showed that 31 of the 162 differential metabolites between the model group and sham operation group were significantly adjusted after administration of Erzhiwan， which were mainly glycerol phospholipid metabolites. Pathway enrichment results showed that Erzhiwan mainly affected glycerophospholipid metabolic pathway， PI3K-Akt pathway， cyclic guanosine monophosphate（cGMP）-protein kinase G（PKG） pathway and other metabolic pathways. Compared with the sham operation group， the levels of phosphatidylcholine（PC， 11 types） and phosphatidylethanolamine（PE， 5 types） in mouse myocardial tissue of the model group were increased（P<0.05， P<0.01）， and the mRNA and protein expressions of PI3K and p-Akt were decreased（P<0.05， P<0.01）. Compared with the model group， the levels of PC（11 types） and PE（5 types） were decreased（P<0.05， P<0.01） in myocardial tissue of Erzhiwan group， the mRNA and protein expressions of PI3K and p-Akt were elevated（P<0.01）. ConclusionErzhiwan can alleviate the pathological injury of myocardium in ovariectomized mice， improve the abnormal cardiac function， improve lipid metabolism disorder， and reduce the levels of myocardial injury markers and inflammatory factors， which involves a number of signaling and metabolic pathways in the heart， among which glycerophospholipid metabolism pathway and PI3K/Akt pathway may have key roles.

Background Psychological disturbances such as work-family conflict and depressive mood are prevalent among occupational groups and are closely related to eating behavior. Therefore, investigating the influencing factors of eating behavior is of great significance for promoting the health behaviors of occupational populations. Objective To clarify the current situation of eating behavior among the occupational populations aged 18 to 60 years in China, and to explore the relationship between work-family conflict, depressive mood, and eating behavior, and to test the mediating role of depressive mood in the relationship. Methods The study used a data set containing occupational populations aged 18 to 60 years extracted from the 2021 Psychology and Behavior Investigation of Chinese Residents. The Work-Family Conflict Scale, the Chinese version of the Sakata Eating Behavior Scale Short Form, and the Patient Health Questionnaire-Depression Scale were used. Potential influencing factors of eating behavior of the occupational populations were evaluated by multiple linear regression. Structural equation modeling was used to analyze the relationships between work-family conflict, depressive mood, and eating behavior, and the Bootstrap method was used to test the mediating effect of depressive mood on the relationship of work-family conflict and eating behavior. Results Among the occupational populations, the proportion of reporting high work-family conflict was 48.4%, and the proportion of reporting mild depression and above was 48.7%. The total score of eating behavior was (16.16±4.64), and the proportion of high abnormal eating behavior tendency was 39.1%. There were significant differences in eating behavior score among different age, educational level, marital status, number of offspring, occupation, smoking, and drinking groups (P<0.05). The partial correlation analysis showed that work-family conflict and depressive mood were positively correlated with abnormal eating behavior (r=0.367, 0.386, P<0.001); work-family conflict was positively correlated with depressive mood (r=0.466, P<0.001). The results of the multiple linear regression showed that depressive mood, work-family conflict, age, smoking, drinking, and education level were associated with eating behavior (P<0.05). The structural equation modeling indicated that work-family conflict positively associated with depressive mood (b=0.529, P<0.001), depressive mood positively associated with abnormal eating behavior (b=0.292, P<0.001), and work-family conflict positively associated with abnormal eating behavior (b=0.270, P<0.001). Depressive mood played a partial mediating role in the relationship between work-family conflict and eating behavior, and the effect value was 0.154 (95%CI: 0.132, 0.179) that accounted for 36.32% of the total effect. Conclusion Work-family conflict could directly affect the eating behavior among occupational populations, and also indirectly affect eating behavior through a mediating effect of depressive mood. Therefore, optimizing the allocation of tasks between work and family, providing psychological support in need, alleviating work-family conflict and depressive mood may improve the eating behavior and mental health of working populations.

BACKGROUND: Several studies have demonstrated the occurrence of secondary tumors as a rare but significant complication of chimeric antigen receptor T (CAR-T) cell therapy, underscoring the need for a detailed investigation. Given the limited variety of secondary tumor types reported to date, a comprehensive characterization of the various secondary tumors arising after CAR-T therapy is essential to understand the associated risks and to define the role of the immune microenvironment in malignant transformation. This study aims to characterize the immune microenvironment of a newly identified secondary tumor post-CAR-T therapy, to clarify its pathogenesis and potential therapeutic targets. METHODS: In this study, the bone marrow (BM) samples were collected by aspiration from the primary and secondary tumors before and after CD19 CAR-T treatment. The CD45 + BM cells were enriched with human CD45 microbeads. The CD45 + cells were then sent for 10× genomics single-cell RNA sequencing (scRNA-seq) to identify cell populations. The Cell Ranger pipeline and CellChat were used for detailed analysis. RESULTS: In this study, a rare type of secondary chronic myelomonocytic leukemia (CMML) were reported in a patient with diffuse large B-cell lymphoma (DLBCL) who had previously received CD19 CAR-T therapy. The scRNA-seq analysis revealed increased inflammatory cytokines, chemokines, and an immunosuppressive state of monocytes/macrophages, which may impair cytotoxic activity in both T and natural killer (NK) cells in secondary CMML before treatment. In contrast, their cytotoxicity was restored in secondary CMML after treatment. CONCLUSIONS This finding delineates a previously unrecognized type of secondary tumor, CMML, after CAR-T therapy and provide a framework for defining the immune microenvironment of secondary tumor occurrence after CAR-T therapy. In addition, the results provide a rationale for targeting macrophages to improve treatment strategies for CMML treatment.
Humans ; Lymphoma, Large B-Cell, Diffuse/therapy* ; Tumor Microenvironment/genetics* ; Antigens, CD19/metabolism* ; Leukemia, Myelomonocytic, Chronic/genetics* ; Immunotherapy, Adoptive/adverse effects* ; Male ; Single-Cell Analysis/methods* ; Female ; Sequence Analysis, RNA/methods* ; Receptors, Chimeric Antigen ; Middle Aged

Background Depressive moods among occupational population are prevalent, which seriously affect their mental-physical health and socioeconomic productivity. This has become an urgent public health concern. Objective To understand current situation of depressive mood among an occupational population aged 18 to 60 covering 120 cities of China, and to explore the relationship between work-family conflict and depressive mood as well as the role of life stress in the relationship, as to provide a scientific basis for developing measures to reduce depressive mood in the occupational population. Methods Using the data of the Psychology and Behavior Investigation of Chinese Residents in 2021, an occupational population aged 18 to 60 years was selected as study subjects. A total of 3785 subjects were included in the study. The Work-Family Conflict Scale, Subjective Life Stress Scale, and Patient Health Questionnaire-Depression Scale were used to assess the work-family conflict, life stress, and depressive mood of the subjects. Harman's single-factor method was used to evaluate common method bias in the survey data. One-way ANOVA was applied to test the difference in work-family conflict, life stress, and depressive mood among occupational population by demographic characteristics, and chi-square test was used to analyze the difference in reporting depressive mood. Partial correlation analysis was used to evaluate the correlation between selected variables. Process plug-in was used to test potential mediating effect of life stress on work-family conflict and depressive emotion. Results The scores of work-family conflict, life stress, and depressive mood among the occupational population were 24.60±8.28, 9.28±3.78, and 5.43±5.30, respectively. The prevalence rates of depressive mood was 48.7% (1888/3875). The score of depressive mood among occupational population who never smoked was significantly higher than that of those who smoked (P<0.01). The partial correlation analysis showed that work-family conflict and life stress were positively correlated with depressive mood (r=0.472 and 0.447, P<0.001); work-family conflict was positively correlated with life stress (r=0.361, P<0.001). The mediation analysis results showed that work-family conflict positively associated with life stress (b=0.361, P<0.001); life stress positively associated with depressive mood (b=0.318, P<0.001); work-family conflict positively associated with depressive mood (b=0.357, P<0.001), and played a partial mediating role in the relationship between work-family conflict and depressive mood with an effect size of 0.115 (95%CI: 0.099, 0.130) that accounted for 24.36% of the total effect. Conclusion Work-family conflict may not only directly affect depressive mood among occupational population, but also indirectly affect depressive mood through a mediating effect of life stress.

Objective To analyze the status of persistent human papillomavirus (HPV) infection and the distribution of viral subtypes in the Zhengzhou region. Methods Clinical data of 55239 patients who underwent HPV-DNA genotyping tests from 2018 to 2024 were collected. On the basis of HPV follow-up results, patients were divided into three groups: 849 cases of infection with the same HPV type, 255 cases of persistent infection with different HPV types, and 857 cases of transient HPV infection. Results Among the 9232 initially-screened patients who were positive with HPV, the high-risk HPV (HR-HPV) positive rate was 84.6% (7813/9232), and predominant subtypes were HPV-16 (20.8%), HPV-52 (17.2%), and HPV-53 (9.6%). The low-risk HPV (LR-HPV) positive rate was 15.4% (1419/9232), mainly HPV-81 (28.1%) and HPV-42 (27.0%). Among the 1961 follow-up cases, the rates of persistent and non-persistent infections with the same HPV type were 35.7% (701/1961) and 7.5% (148/1961), respectively. The rates of persistent and non-persistent infections with different HPV types were 10.9% (214/1961) and 2.1% (41/1961), respectively. Meanwhile, 43.7% (857/1961) tested negative upon follow-up. Among the 701 cases of persistent infection with the same HPV type, HR-HPV accounted for 85.7% (601/701), and LR-HPV accounted for 14.3% (100/701). Among the 214 cases of persistent infection with different HPV types, 89.7% (192/214) were high-risk transitions, and 10.3% (22/214) were low-risk transitions. Regardless of HPV types, HR-HPV was more likely to cause persistent infection than LR-HPV. In addition, over 60% of HR-HPV persistent infections resolved within 18 months, 30% developed into persistent infections, and only 15% of patients had persistent infections that last more than 24 months. Conclusion Persistent HPV infections are predominantly high-risk types. Most patients clear the infection within 18 months, approximately 30% develop persistent infections, and about 15% of patients have persistent infections that last more than 24 months. However, the HR-HPV persistent infection rates across different age groups slightly differ.

Objective To analyze the spatial and temporal distribution characteristics of hand-foot-mouth disease (HFMD) in Zibo City, to explore the key incidence areas, and to find a suitable prediction model, so as to provide reference for the prevention and control of HFMD. Methods The spatiotemporal clustering characteristics of HFMD in Zibo City from 2018 to 2023 were analyzed by using SaTScan 10.0.2 software and ArcGIS 10.7 software. A combination model of ARIMA and SVM was established, and the prediction results were verified and compared. Results Spatial clustering analysis showed that there was spatial clustering of the incidence of HFMD in various townships of Zibo City from 2020 to 2022. The high-high clustering areas and Getis-Ord hot spot areas were mainly concentrated in some main urban areas of Zhangdian District, Zichuan District, and Huantai County. A total of 2-5 aggregation areas were detected by spatiotemporal scanning analysis. The first-type aggregation areas were mainly concentrated in the towns of Zhangdian District, Huantai County, Linzi District, Zhoucun District and Gaoxin District. The aggregation months were July, August, September and November. The model prediction results showed that the ARIMA-SVM combined model was more accurate than the traditional ARIMA model. Conclusion There is a spatiotemporal clustering of hand-foot-mouth disease in Zibo City. The ARIMA-SVM combined model can be used to predict the incidence of hand-foot-mouth disease in Zibo City, and to strengthen health education and disease monitoring in high-risk areas and populations during the epidemic months.

In recent years, the wearable device market has been developing rapidly. Wearable devices with personalized health management and chronic disease monitoring are widely used in daily life by virtue of their powerful performance and convenience. However, with the popularization of these devices, skin adverse reactions caused by prolonged wearable wear are gradually increasing, among which allergic contact dermatitis (ACD) is the most common. Common allergens such as acrylates, methacrylates, rosin, chromium and nickel are widely present in adhesives and device components and are the main causes of ACD. Understanding the presence of potential sensitizers in wearable devices can help in diagnostic patch testing in users experiencing skin reactions caused by the device. Future innovations in wearable device materials will focus on the adoption of safer bonding technologies and biocompatible materials to reduce the risk of allergy. The introduction of new materials brings both development opportunities and challenges. Educating users on proper device usage, identifying specific allergens, selecting hypoallergenic materials, and optimizing device maintenance are important for reducing the risk of ACD.

Objective:To develop an artificial intelligence (AI)-based platelet review strategy to identify abnormal platelet histograms with no significant difference between initial impedance platelet count (PLT-I) and PLT-F results.Methods:This study included 5 119 routine blood analysis in Nanfang Hospital of Southern Medical University and its Ganzhou branch from July 2023 and March 2024. Specimens exhibiting abnormal platelet histograms and an initial platelet count >40×10?/L underwent review using the fluorescent platelet count (PLT-F) channel. Consistency of the results was defined as a difference between impedance platelet count (PLT-I) and PLT-F less than ±20% of the PLT-F results. A deep learning model was developed using platelet and red blood cell histogram data from a training set of 3 807 specimens. The model′s diagnostic performance was evaluated on an independent external validation set ( n=805) using receiver operating characteristic (ROC) curve analysis. Changes in the number of reviewed samples and sample turnaround time were analyzed to assess its clinical utility. Results:The deep learning model based on platelet and red blood cell histograms achieved an area under the ROC curve (AUC) of 0.854 in the training set. At a cutoff value of 0.1, the sensitivity was 0.954 and specificity was 0.358. The model could reduce review by 16.80% (190/1 131). In the validation set, the AUC was 0.805, with a sensitivity of 0.955 and specificity of 0.307, corresponding to a reduction of 17.41% (47/270) in reviewed specimens.Conclusion:The platelet review prediction model developed based on deep learning technology can efficiently identify samples with consistent results before and after review, reducing unnecessary reviews and shortening specimen testing time, thereby improving the efficiency of platelet test.

Objective:To investigate the methodological differences in the detection, the inflammatory markers and the pathogenic epidemiological characteristics of influenza A virus in clinical laboratories, in order to provide more diagnostic and epidemiological data for diagnosis and prevention for children with influenza A.Methods:A retrospective cross-sectional study was conducted to collect 96 731 patients with suspected influenza A from January 2016 to October 2024 in Nanyang City Center Hospital from the Clinical Laboratory Testing Information System, including 5 731 patients with confirmed influenza A, aged 5.2 (2.8, 43.7) years old. We analyzed the distribution of influenza A patients from age and mixed infections, the relationship between patient age and positive detection rate by restricted cubic spline (RCS), analyzed differences in testing methods used Kappa consistency testing and receiver operating characteristic (ROC) curves, established a model of inflammatory markers by logistic regression, as well as developed a prediction model and also the mutation of the hemagglutinin (HA) sequence of the influenza A subtype H3N2 virus using evolutionary tree analysis.Results:RCS analysis showed an inverted 'S' shaped non-linear relationship between the positive detection rate of influenza A and the age groups of the patients. Among the mixed infections, 1.43%(1 352/94 867) of the cases were combined with Mycoplasma pneumoniae infection. The Kappa values of reverse transcription PCR (RT-PCR) and serological indirect immunofluorescence assay (IFA) for detecting influenza A in nasopharyngeal swabs and alveolar lavage fluid in clinical laboratories were 0.632 and 0.809, respectively, and those of magnetic particle chemiluminescence assay were 0.614 and 0.668, respectively, and the area under curves in ROC curve of IFA and RT-PCR were 0.869 and 0.792, respectively. The inflammatory indexes were usually elevated in severe children compared with mild children. By binary logistic regression model analysis, neutrophil-to-lymphocyte ratio, D-dimer/fibrinogen and prognosis nutrition index were the risk factors and serum amyloid A/C reactive protein ratio was the protective factor for severe children with influenza A, and the OR values of the above factors were 1.760, 7.076, 1.045, and 0.719, respectively, and P<0.01. By the Bayesian Interdiction Criterion, the optimal seasonal autoregressive moving average mixed model for influenza A epidemics was ARIMA (1, 1, 1) (2, 1, 2) 12 with the highest prediction accuracy of 98.63%. The seven strains of H3N2 all belonged to the same isoforms, with nucleotide similarity of the HA gene ranging from 99.5% to 99.9%, and the glycosylation site, receptor-binding site, and the conserved amino acid residue Glycosylation sites, receptor binding sites and conserved amino acid residues remained unchanged. HA sequence analysis showed that the prevalent strains in Nanyang had undergone mutation to different degree compared with the vaccine strains. Conclusion:Scientific and rational testing and characteristic inflammatory markers in the clinical laboratory are of great clinical value in the diagnosis of children with severe influenza A. At the same time, the epidemiological monitoring of influenza A variants should be strengthened.

Objective:To compare the changes in fracture displacement under different vertical loadings between the 2 different internal fixation modalities for vertically unstable femoral neck fractures of Pauwels type Ⅲ by a mechanical study and a finite element analysis.Methods:Twelve biomimic bones were transversely dissected from 10 cm below the lesser trochanter of the femur to create femoral neck fracture models with a Pauwels angle of 70° using a swing saw. The models were equally divided into 2 groups ( n=6): group A was fixed with 3 cannulated screws after fracture reduction (scheme A), and group B with 3 cannulated screws plus a self-designed anteromedial support plate after fracture reduction (scheme B). Continuous vertical force was applied using a mechanical testing machine. Changes in displacement were recorded and load-displacement curves were plotted. One volunteer (female, 28 years old, 168 cm in height and 65 kg in weight) was selected for finite element analysis of her CT images of both lower limbs to examine the maximum displacement and the maximum Mises stress in scheme A and scheme B respectively. Results:In groups A and B respectively: All the 6 biomimic mimetic bones had similar load and displacement curves, and similar fracture displacements (Dx) at different loading points (N X); the curves of 6 biomimic bones were highly fitted with S-shaped curve equation (the r-square value was close to 1). At the initial loading stage (0 N0.05). When the load was 100 N